Open AccessDG planning in stand‐alone microgrid considering stochastic characteristic
Author(s) -
Fang Wanliang,
Liu Haoming,
Chen Feng,
Zheng Hao,
Hua Guanghui,
He Weiguo
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0515
Subject(s) - microgrid , photovoltaic system , voltage , battery (electricity) , control theory (sociology) , compensation (psychology) , computer science , boundary (topology) , mathematical optimization , distributed generation , genetic algorithm , state of charge , monte carlo method , function (biology) , power (physics) , engineering , renewable energy , mathematics , electrical engineering , control (management) , artificial intelligence , psychoanalysis , mathematical analysis , biology , psychology , quantum mechanics , evolutionary biology , statistics , physics
To deploy distributed generation (DG) properly in the stand‐alone microgrid, a multi‐type DG planning model considering stochastic characteristic of photovoltaic (PV), wind turbine (WT) and load is established. The annual total cost including the investment cost of DG, the maintenance cost, the fuel cost and the environment compensation cost is taken as objective function, and node voltage boundary, state of charge of battery storage boundary are taken as the main constraints. According to the probability density function of PV, WT and load, the voltage violation ratio of nodes in microgrid is calculated by the probability power flow based on Monte Carlo method. Finally, the optimisation model is solved by the genetic algorithm. The simulation results of a 33‐bus microgrid system case show that the proposed plan strategy has good performance in economy.